USNA-UMBC-Project Receiver - Add noise to CAN-bus received data and Implement Kalman Filter
Dependencies: ServoOut mcp2515 BNO055
Revision 1:5794ff4efa9a, committed 2022-05-20
- Comitter:
- professorrodriguezse
- Date:
- Fri May 20 18:37:10 2022 +0000
- Parent:
- 0:ee3eb98ec375
- Commit message:
- USNA-UMBC-KalmanFilter-ReceiverSide
Changed in this revision
diff -r ee3eb98ec375 -r 5794ff4efa9a NODE-KF-2-v2-noise.cpp --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/NODE-KF-2-v2-noise.cpp Fri May 20 18:37:10 2022 +0000 @@ -0,0 +1,169 @@ +/* +Sends and Reads position of servos in degrees and prints them all. + */ + +#include "mbed.h" +#include "platform/mbed_thread.h" +//#include "BNO055.h" +#include "CAN3.h" +//#include "ServoOut.h" +#include "gtrackMatrix.c" +#include "time.h" + +int myID = 2; + +Serial pc(USBTX, USBRX); //pc serial (tx, rx) uses USB PA_9 and PA_10 on Nucleo D1 and D0 pins +//BNO055 bno(D4, D5); +SPI spi(D11, D12, D13); // mosi, miso, sclk +CAN3 can3(spi, D10, D2); // spi bus, CS for MCP2515 controller +//ServoOut servoOut1(A0); //A0); // PA_0 is the servo output pulse + +CANMessage canTx_msg; +CANMessage canRx_msg; + +Timer t; + +int main() +{ + srand(time(0)); + thread_sleep_for(500); + float currTime, dt, ytrue, y; + float T = 0.017; //s + t.start(); + pc.baud(115200); + pc.printf("Starting Program... \n\r"); + //can3.reset(); // reset the can bus interface + can3.frequency(500000); // set up for 500K baudrate + char msg_send[8]; + char msg_read_char[8]; + thread_sleep_for(1000); + + int n = 2; //# states + int p = 2; //# outouts + int rows=n; + int m=2; + int cols=n; + + float A[2][2]= {{0.0,1.0},{0.0,0.0}}; + float B[2][2]= {{0.0,0.0},{0.0,1.0}}; + float C[1][2]= {{1.0,0.0}}; + float Phi[n][n]; + float Eye[n][n]; + float tempMatrix[n][n]; + float tempMatrix2[n][n]; + float tempMatrix3[n][n]; + float tempMatrix4[n][n]; + gtrack_matrixEye(n, *Eye); + gtrack_matrixScalarMultiply(rows, cols, *A, T, *tempMatrix); + gtrack_matrixAdd(rows, cols, *Eye, *tempMatrix, *Phi); + + float Gam[n][n]; + gtrack_matrixScalarMultiply(rows, cols, *B, T, *tempMatrix); + gtrack_matrixScalarMultiply(rows, cols, *B, T*T/2, *tempMatrix2); + gtrack_matrixMultiply(rows, m, cols, *A, *tempMatrix2, *tempMatrix3); + gtrack_matrixAdd(rows, cols, *tempMatrix, *tempMatrix3, *Gam); + pc.printf("\n\r Gamma: \n\r"); + gtrack_matrixPrint(rows, cols, *Gam); + //pc.printf("%.4f \t %.4f \t %.4f \t %.4f\n\r",Gam[0][0],Gam[0][1],Gam[1][0],Gam[1][1]); + + float sig_w=1; //Measurement noise parameter + float sig_v=50; //Trial process noise parameters + float Q[n][n]; + float R = sig_w*sig_w; + gtrack_matrixScalarMultiply(rows, cols, *Eye, sig_v*sig_v, *Q); + float hatx_0[2][1] = {{0},{0}}; + float varx_0[n][n]; + float P_0[n][n]; + gtrack_matrixScalarMultiply(rows, cols, *Q, 1, *varx_0); + gtrack_matrixScalarMultiply(rows, cols, *varx_0, 1, *P_0); + pc.printf("P_0: \n\r"); + gtrack_matrixPrint(rows, cols, *P_0); + //pc.printf("%.4f \t %.4f \t %.4f \t %.4f\n\r",P_0[0][0],P_0[0][1],P_0[1][0],P_0[1][1]); + + float xhat_nminus1[n][1]; + gtrack_matrixScalarMultiply(n, 1, *hatx_0, 1, *xhat_nminus1); + float P_nminus1[n][n]; + gtrack_matrixScalarMultiply(n, n, *P_0, 1, *P_nminus1); + float y_minus1[1][1]; + gtrack_matrixMultiply(1, 2, 1, *C, *hatx_0, *y_minus1); + pc.printf("y_minus1: \n\r"); + gtrack_matrixPrint(1, 1, *y_minus1); + + float xhat_n_pre[n][1]; + float P_n_pre[n][n]; + float yhat_n[1][1]; + float S; + float epsilon = 0.00001; + int count = 0; + + float tempVector[1][n]; + float tempScalar[1][1]; + float KFGain[n][1]; + float tempVector2[n][1]; + float P_n[n][n]; + float xhat_n[n][1]; + pc.printf("Sample: \t Time: \t Yaw: \t Yaw+Noise: \t Estimate: \t KFGain: (1) and (2)\n\r"); + while(1) { + currTime = t.read(); + count = count +1; + if (count > 2000) { + break; + } + while(1) { + if(can3.read(&canRx_msg) == CAN_OK) { + if(canRx_msg.id == 1) { + for (int i = 0; i < 8; i++) { + msg_read_char[i] = (char)canRx_msg.data[i]; + } + sscanf(msg_read_char, "%f", &ytrue); + y = ytrue + ((rand() % 100) - 50)/10; + gtrack_matrixMultiply(n, n, 1, *Phi, *xhat_nminus1, *xhat_n_pre); //xhat_n_pre=Phi*xhat_nminus1 + gtrack_matrixMultiply(n, n, n, *Gam, *Q, *tempMatrix); //Gam*Q + gtrack_matrixTransposeMultiply(n, n, n, *tempMatrix, *Gam, *tempMatrix2); //Gam*Q*Gam' + gtrack_matrixMultiply(n, n, n, *Phi, *P_nminus1, *tempMatrix); //Phi*P_nminus1 + gtrack_matrixTransposeMultiply(n, n, n, *tempMatrix, *Phi, *tempMatrix3); //Phi*P_nminus1*Phi' + gtrack_matrixAdd(n, n, *tempMatrix2, *tempMatrix3, *P_n_pre); //P_n_pre=Phi*P_nminus1*Phi'+Gam*Q*Gam' + gtrack_matrixMultiply(1, 2, 1, *C, *xhat_n_pre, *yhat_n); + //pc.printf("yhat_n: %.4f\n\r", yhat_n[0][0]); + + gtrack_matrixMultiply(1, 2, 2, *C, *P_n_pre, *tempVector); + gtrack_matrixTransposeMultiply(1, 2, 1, *tempVector, *C, *tempScalar); + S = tempScalar[0][0] + R; + if ((S >= -1*epsilon) && (S <= 1*epsilon)) { + pc.printf("Alert!!! S is very small %.8f \n\r", S); + if (S > 0) { + S = epsilon; + } else { + S = -1*epsilon; + } + } + + gtrack_matrixTransposeMultiply(2, 2, 1, *P_n_pre, *C, *tempVector2); + gtrack_matrixScalarMultiply(2, 1, *tempVector2, 1/S, *KFGain); + //pc.printf("S: %.5f \t KFGain: %.4f, %.4f\n\r", S, KFGain[0][0], KFGain[1][0]); + + gtrack_matrixMultiply(2, 1, 2, *KFGain, *C, *tempMatrix); + gtrack_matrixSub(n, n, *Eye, *tempMatrix, *tempMatrix2); + gtrack_matrixMultiply(n,n,n, *tempMatrix2, *P_n_pre, *P_n); + + gtrack_matrixMultiply(1,2,1, *C, *xhat_n_pre, *tempScalar); //C*xhat_n_pre + tempScalar[0][0] = y - tempScalar[0][0]; + gtrack_matrixScalarMultiply(2, 1, *KFGain, tempScalar[0][0], *tempVector2); + gtrack_matrixAdd(2,1, *xhat_n_pre, *tempVector2, *xhat_n); // xhat_n=xhat_n_pre+KFGain*(y-C*xhat_n_pre); + //pc.printf("xhat_n: %.4f, %.4f\n\r", xhat_n[0][0], xhat_n[1][0]); + + gtrack_matrixScalarMultiply(2, 1, *xhat_n, 1, *xhat_nminus1); + gtrack_matrixScalarMultiply(2, 2, *P_n, 1, *P_nminus1); + y_minus1[0][0] = y; + + pc.printf("%d \t %.3f \t %.1f \t %.1f \t %.4f \t %.4f \t %.4f\n\r", count, t.read(), ytrue, y, xhat_n[0][0], KFGain[0][0], KFGain[1][0]); + dt = T-(t.read()-currTime); + if (dt > 0) { + thread_sleep_for(dt*1000); + } + break; + } + } + } + }//while(1) +}//main \ No newline at end of file
diff -r ee3eb98ec375 -r 5794ff4efa9a Nucleo_L432KC_CAN3_BNO_Servo_EW485A.cpp --- a/Nucleo_L432KC_CAN3_BNO_Servo_EW485A.cpp Thu Jul 22 23:05:18 2021 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,113 +0,0 @@ -/* mbed Microcontroller Library - * Copyright (c) 2019 ARM Limited - * SPDX-License-Identifier: Apache-2.0 - */ -// Program to test the CAN bus using SPI on the L432KC Nucleo board -// to an MCP2551 CAN transceiver bus IC using https://os.mbed.com/users/tecnosys/code/mcp2515/ - -// J. Bradshaw 20210512 -#include "mbed.h" -#include "platform/mbed_thread.h" -#include "CAN3.h" -#include "BNO055.h" -#include "ServoOut.h" - -#define THIS_CAN_ID 0x05 //Address of this CAN device -#define DEST_CAN_ID 0 //Address of destination - -Serial pc(USBTX, USBRX); //pc serial (tx, rx) uses USB PA_9 and PA_10 on Nucleo D1 and D0 pins -BNO055 bno(D4, D5); -SPI spi(D11, D12, D13); // mosi, miso, sclk -CAN3 can3(spi, D10, D2); // spi bus, CS for MCP2515 controller -ServoOut servoOut1(PA_0); //A0); // PA_0 is the servo output pulse -AnalogIn ain3(A3); - -unsigned char can_txBufLen = 0; -unsigned char can_tx_buf[8] = {0, 0, 0, 0, 0, 0, 0, 0}; -CANMessage canTx_msg; - -unsigned char can_rx_bufLen = 8; -unsigned char can_rx_buf[8]; -unsigned short can_rxId = 0; -CANMessage canRx_msg; - -Timer t; - -void bno_init(void){ - if(bno.check()){ - pc.printf("BNO055 connected\r\n"); - bno.setmode(OPERATION_MODE_CONFIG); - bno.SetExternalCrystal(1); - //bno.set_orientation(1); - bno.setmode(OPERATION_MODE_NDOF); //Uses magnetometer - //bno.setmode(OPERATION_MODE_NDOF_FMC_OFF); //no magnetometer - bno.set_angle_units(RADIANS); - } - else{ - pc.printf("BNO055 NOT connected\r\n Program Trap."); - while(1); - } -} - -int main() { - thread_sleep_for(500); - - t.start(); - pc.baud(115200); - bno_init(); - //can3.reset(); // reset the can bus interface - can3.frequency(500000); // set up for 500K baudrate - - servoOut1.pulse_us = 1500; - - pc.printf("CAN MCP2515 test: %s\r\n", __FILE__); - while(1) { - - servoOut1.pulse_us = 1000 + (1000.0*ain3); - - bno.get_angles(); - - pc.printf("%.2f %.2f %.2f\r\n",bno.euler.roll, bno.euler.pitch, bno.euler.yaw); - //sprintf(can_rx_buf, "b%.2f\r\n", bno.euler.yaw); //format output message string - can_tx_buf[0] = bno.euler.rawroll & 0x00ff; - can_tx_buf[1] = (bno.euler.rawroll >> 8) & 0x00ff; - can_tx_buf[2] = bno.euler.rawpitch & 0x00ff; - can_tx_buf[3] = (bno.euler.rawpitch >> 8) & 0x00ff; - can_tx_buf[4] = bno.euler.rawyaw & 0x00ff; - can_tx_buf[5] = (bno.euler.rawyaw >> 8) & 0x00ff; - can_tx_buf[6] = 0; - can_tx_buf[7] = 0; - - // CAN write message - for(int i=0;i<8;i++){ - canTx_msg.data[i] = can_tx_buf[i]; - } - canTx_msg.id = THIS_CAN_ID; //(rand() % 0xff); // Randomize transmit ID or THIS_CAN_ID; - - can3.write(&canTx_msg); - pc.printf("%.2f CAN TX id=%02X data: ", t.read(), canTx_msg.id); - for(int i=0;i<8;i++){ - pc.printf(" %2X", can_tx_buf[i]); - } - pc.printf("\r\n"); - //set up a random delay time of up to .79 seconds - //delayT = ((rand() % 7) * 31.0) + ((rand() % 9) * .1) + runTime.sec_total; - - // CAN receive message - if(can3.read(&canRx_msg) == CAN_OK){ //if message is available, read into msg - pc.printf("CAN RX id=0x%02X data: ", canRx_msg.id); - for (int i = 0; i < canRx_msg.len; i++) { - pc.printf(" %2X", canRx_msg.data[i]); - } - pc.printf("\r\n"); - } - - //if(canTxErrors > 50){ -// can.reset(); -// } -// if(canRxErrors > 50){ -// can.reset(); -// } - thread_sleep_for(50); - }//while(1) -}//main
diff -r ee3eb98ec375 -r 5794ff4efa9a gtrackMatrix.c --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/gtrackMatrix.c Fri May 20 18:37:10 2022 +0000 @@ -0,0 +1,606 @@ +/** +* @b Description +* @n +* This function is used to create identity matrix +* +* @param[in] size +* Size of identity matrix +* @param[out] A +* Matrix A(size,size) = eye(size) +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixEye(int size, float *A) +{ + /* A(size*size) = eye(size) */ + int i; + + for (i = 0U; i < size*size; i++) { + A[i] = 0.f; + } + + for (i = 0U; i < size; i++) { + A[i+i*size] = 1.0f; + } +} + +/** +* @b Description +* @n +* This function is used to initialise matrix to a value +* +* @param[in] rows +* Number of rows +* @param[in] cols +* Number of cols +* @param[in] value +* value to set +* @param[out] A +* Matrix A(rows,cols) = ones(rows,cols)*value +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixInit(int rows, int cols, float value, float *A) +{ + /* A(rows*cols) = ones(rows,cols)*value */ + int i; + + for (i = 0U; i < rows*cols; i++) { + A[i] = value; + } +} + +/** +* @b Description +* @n +* This function is used to create diagonal square matrix +* +* @param[in] size +* Size of square matrix +* @param[in] v +* Diagonal vector +* @param[out] A +* Matrix A(size,size) = diag(v(size)) +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixSetDiag(int size, float *v, float *A) +{ + /* A(size*size) = diag(v(size)) */ + int i; + + for (i = 0U; i < size*size; i++) { + A[i] = 0; + } + + for (i = 0U; i < size; i++) { + A[i+i*size] = v[i]; + } +} + +/** +* @b Description +* @n +* This function is used to get diagonal from the square matrix +* +* @param[in] size +* Size of square matrix +* @param[in] A +* Matrix A(size,size) +* @param[out] v +* Diagonal vector, v(size) = diag(A(size*size)) +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixGetDiag(int size, float *A, float *v) +{ + /* v(size) = diag(A(size*size)) */ + int i; + for (i = 0U; i < size; i++) { + v[i] = A[i+i*size]; + } +} + +/** +* @b Description +* @n +* This function is used to multiply two matrices. +* Matrices are all real, single precision floating point. +* Matrices are in row-major order +* +* @param[in] rows +* Outer dimension, number of rows +* @param[in] m +* Inner dimension +* @param[in] cols +* Outer dimension, number of cols +* @param[in] A +* Matrix A +* @param[in] B +* Matrix B +* @param[out] C +* Matrix C(rows,cols) = A(rows,m) X B(cols,m)T +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixMultiply(int rows, int m, int cols, float *A, float *B, float *C) +{ + /* C(rows*cols) = A(rows*m)*B(m*cols) */ + int i,j, k; + for (i = 0; i < rows; i++) { + for (j = 0; j < cols; j++) { + C[i*cols + j] = 0; + for (k = 0; k < m; k++) { + C[i*cols+j] += A[i*m+k] * B[k*cols + j]; + } + } + } +} + +/** +* @b Description +* @n +* This function is used to multiply two matrices. Second Matrix is getting transposed first +* Matrices are all real, single precision floating point. +* Matrices are in row-major order +* +* @param[in] rows +* Outer dimension, number of rows +* @param[in] m +* Inner dimension +* @param[in] cols +* Outer dimension, number of cols +* @param[in] A +* Matrix A +* @param[in] B +* Matrix B +* @param[out] C +* Matrix C(rows,cols) = A(rows,m) X B(cols,m)T +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixTransposeMultiply(int rows, int m, int cols, float *A, float *B, float *C) +{ + /* C(rows*cols) = A(rows*m)*B(cols*m)T */ + int i,j, k; + for (i = 0; i < rows; i++) { + for (j = 0; j < cols; j++) { + C[i*cols + j] = 0; + for (k = 0; k < m; k++) { + C[i*cols+j] += A[i*m+k] * B[k + j*m]; + } + } + } +} + +/** +* @b Description +* @n +* This function is used to multiply matrix by a scalar. +* Matrices are all real, single precision floating point. +* Matrices are in row-major order +* +* @param[in] rows +* Number of rows +* @param[in] cols +* Number of cols +* @param[in] A +* Matrix A +* @param[in] c +* Scalar c +* @param[out] B +* Matrix B(rows,cols) = A(rows,cols) * c +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixScalarMultiply(int rows, int cols, float *A, float c, float *B) +{ + /* B(rows*cols) = A(rows*cols)*C */ + int i; + for (i = 0U; i < rows*cols; i++) { + B[i] = A[i] * c; + } +} + +/** +* @b Description +* @n +* This function is used to add two matrices. +* Matrices are all real, single precision floating point. +* Matrices are in row-major order +* +* @param[in] rows +* Number of rows +* @param[in] cols +* Number of cols +* @param[in] A +* Matrix A +* @param[in] B +* Matrix B +* @param[out] C +* Matrix C(rows,cols) = A(rows,cols) + B(rows,cols) +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixAdd(int rows, int cols, float *A, float *B, float *C) +{ + /* C(rows*cols) = A(rows*cols) + B(rows*cols) */ + int i; + for (i = 0U; i < rows*cols; i++) { + C[i] = A[i] + B[i]; + } +} + +/** +* @b Description +* @n +* This function is used to subtract two matrices. +* Matrices are all real, single precision floating point. +* Matrices are in row-major order +* +* @param[in] rows +* Number of rows +* @param[in] cols +* Number of cols +* @param[in] A +* Matrix A +* @param[in] B +* Matrix B +* @param[out] C +* Matrix C(rows,cols) = A(rows,cols) - B(rows,cols) +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixSub(int rows, int cols, float *A, float *B, float *C) +{ + /* C(rows*cols) = A(rows*cols) - B(rows*cols) */ + int i; + for (i = 0U; i < rows*cols; i++) { + C[i] = A[i] - B[i]; + } +} + +/** +* @b Description +* @n +* This function is used to force matrix symmetry by averaging off-diagonal elements +* Matrices are squared, real, single precision floating point. +* Matrices are in row-major order +* +* @param[in] m (m=rows=cols) +* Number of rows and cols +* @param[in] A +* Matrix A +* @param[out] B +* Matrix B +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixMakeSymmetrical(int m, float *A, float *B) +{ + /* Make square matrix symmetrical by averaging off-diagonal elements */ + int i,j; + for (i = 0U; i < m-1; i++) { + B[i*m + i] = A[i*m + i]; + for (j = i+1; j < m; j++) { + B[i*m+j] = B[j*m+i] = 0.5f*(A[i*m+j]+A[j*m+i]); + } + } + B[i*m + i] = A[i*m + i]; +} + + +/** +* @b Description +* @n +* This function is used to initialise vector to a value +* +* @param[in] size +* Size of vector +* @param[in] value +* value to set +* @param[out] A +* Vector A +* +* A(size) = ones(size,1)*value +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_vectorInit(int size, float value, float *A) +{ + /* A(size) = ones(size,1)*value */ + int i; + + for (i = 0U; i < size; i++) { + A[i] = value; + } +} +/** +* @b Description +* @n +* This function adds two vectors +* Vectors are real, single precision floating point. +* +* @param[in] size +* Size of vector +* @param[in] A +* Vector A +* @param[in] B +* Vector B +* @param[out] C +* Vector C = A + B; +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_vectorAdd(int size, float *A, float *B, float *C) +{ + int i; + for (i = 0U; i < size; i++) { + C[i] = A[i] + B[i]; + } +} + +/** +* @b Description +* @n +* This function subtracts two vectors +* Vectors are real, single precision floating point. +* +* @param[in] size +* Size of vectors +* @param[in] A +* Vector A +* @param[in] B +* Vector B +* @param[out] C +* Vector C = A - B; +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_vectorSub(int size, float *A, float *B, float *C) +{ + int i; + for (i = 0U; i < size; i++) { + C[i] = A[i] - B[i]; + } +} + +/** +* @b Description +* @n +* This function multiplies vector by scalar +* Vectors are real, single precision floating point. +* Scalar is real, single precision floating point. +* +* @param[in] size +* Size of vector +* @param[in] A +* Vector A +* @param[in] c +* Scalar c +* @param[out] B +* Vector B = A*c; +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_vectorScalarMul(int size, float *A, float c, float *B) +{ + int i; + for (i = 0U; i < size; i++) { + B[i] = A[i]*c; + } +} + +/** +* @b Description +* @n +* This function performs multiplies vector by scalar and accumulates the results +* Vectors are real, single precision floating point. +* Scalar is real, single precision floating point. +* +* @param[in] size +* Size of vector +* @param[in] A +* Vector A +* @param[in] c +* Scalar c +* @param[in, out] B +* Vector B = B + A*c; +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_vectorScalarMulAcc(int size, float *A, float c, float *B) +{ + int i; + for (i = 0U; i < size; i++) { + B[i] = B[i] + A[i]*c; + } +} + +/** +* @b Description +* @n +* This function performs IIR vector filtering +* Vectors are real, single precision floating point. +* Alpha is real, single precision floating point. +* +* @param[in] size +* Size of vector +* @param[in, out] A +* Vector A +* @param[in] alpha +* Weighting factor for new information, (0<=alpha<=1.0f) +* @param[in] B +* New information vector B +* +* Vector A = A*(1.0f-alpha) + B*alpha; +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_vectorFilter(int size, float *A, float alpha, float *B) +{ + int i; + for (i = 0U; i < size; i++) { + A[i] = A[i]*(1.0f - alpha) + B[i]*alpha; + } +} + + +/** +* @b Description +* @n +* This function accumulates covariance matrix with variances from input vector and mean +* Matrices are all real, single precision floating point. +* Vectors are real, single precision floating point. +* +* @param[in] size +* Size of square matrix +* @param[in] A +* Matrix A +* @param[in] v +* Vector v +* @param[in] mean +* Vector mean +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixCovAcc(int size, float *A, float *v, float *mean) +{ + int i,j; + float d1, d2; + + for (i = 0U; i < size; i++) { + d1 = v[i]-mean[i]; + for (j = i; j < size; j++) { + d2 = v[j]-mean[j]; + A[i*size+j] += d1*d2; + } + } +} + +/** +* @b Description +* @n +* This function normalizes covariance matrix +* Matrices are all real, single precision floating point. +* +* @param[in] size +* Size of square matrix +* @param[in,out] A +* Matrix A +* @param[in] num +* Number of measurments num +* +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ +void gtrack_matrixCovNormalize(int size, float *A, int num) +{ + int i,j; + for (i = 0U; i < size; i++) { + A[i*size+i] /= num; + for (j = i+1; j < size; j++) { + A[i*size+j] /= num; + A[i+j*size] = A[i*size+j]; + } + } +} +/** +* @b Description +* @n +* This function filters covariance matrix +* Matrices are all real, single precision floating point. +* +* @param[in] size +* Size of square matrix +* @param[in,out] A +* Matrix A +* @param[in] B +* Matrix B +* @param[in] alpha +* Filtering coefficient alpha +* Matrix A = (1-alpha)*A + alpha*B +* \ingroup GTRACK_ALG_MATH_FUNCTION +* +* @retval +* None +*/ + +void gtrack_matrixCovFilter(int size, float *A, float *B, float alpha) +{ + int i,j; + for (i = 0U; i < size; i++) { + A[i*size+i] = (1-alpha)*A[i*size+i] + alpha*B[i*size+i]; + for (j = i+1; j < size; j++) { + A[i*size+j] = (1-alpha)*A[i*size+j] + alpha*B[i*size+j]; + A[i+j*size] = A[i*size+j]; + } + } +} + +void gtrack_matrixPrint(int rows, int cols, float *A) +{ + int i,j; + for (i = 0U; i < rows; i++) + { + for (j = 0U; j < cols-1; j++) + { + printf("%6.4f\t", A[i*cols +j]); + } + printf("%6.4f\n\r", A[i*cols +j]); + } + printf("\n\r"); +} \ No newline at end of file